Intelligent or autonomous vehicle is increasingly popular and has recently become a research topic of interest. In autonomous vehicle applications, robust and smooth localization in a large scale outdoor environment is a key problem. For land-based ground vehicle such as an autonomous car which operates in outdoor environment, the most prevalent sensor for localization information is global positioning system (GPS). However, as a commonly known problem, GPS satellite signal is not always available in urban environments and its accuracy is also compromised due to multi-path errors caused by, for example, high city buildings and tree canopies. Therefore, simultaneous localization and mapping (SLAM) based approaches have been increasingly developed to build a map for urban applications. Such approaches aid the inertial navigation by modeling the map and using on-board sensors to localize relative to that map.
All referenced patents, applications and literatures throughout this disclosure are incorporated herein by reference in their entirety. For example, including the following references:    Tim Caselitz, Bastian Stetler, Michael Ruhnke, Wolfram Burgard; Monocular Camera Localization in 3 D LiDAR Maps; ais.informatik.unifreiburge/publications/papers/caselitz 1 6iros.pdf.    Raul Mur-Attal, J. M. M. Montiel, Member, IEEE, and Juan D. Tardos, Member IEEE; ORB-SLAM: A Versatile and Accurate Monocular S L A M System, IEEE Transactions on Robotics, Vol. 31, No. 5, October 2015, 1147-1163.    Torsten Sattler, Akihiko Torii, Josef Sivic, March Pollefeys, Hajime Taira, Masatoshi Okutomi, Tomas Pajdla, Department of Computer Science, E T D Zurich, Tokyo Institute of Technology, Iniria, Microsoft, Redmond, Chezeh Technology University in Prague, Are Large-Scale 3 D Models Really Necessary For Accurate Visual Localization; hal.inria.fr/hal01513083.    Jakob Engel and Thomas Schops and Daniel Cremers, Technical University Munich; LSD-SLAM: Large Scale Direct Monocular SLAM; researchgate.net/publication/290620817_LSD-SLAM_large-scale_direct_monocular_SLAM